Sensor-Fused Radome Diagnostic System

This TACFI funded procurement relates to an SBIR Phase II effort, entitled Radome Operational Performance Evaluation and Tuning with Machine Learning Methods, contract FA8649-22-P-0614. The SBIR effort utilized data measured with sensors mounted on a mobile cobot to create a digital twin, which was then used to calculate radome performance metrics. The original SBIR demonstrated this technology on the F-15 radome. The present effort is related back to this previous SBIR project by significantly advancing the underlying computational capabilities through the refactoring of RayCalc simulations into a high-performance, GPU-accelerated Rust library, directly enhancing the digital twin and performance metric calculations. It also expands the sensor integration and data collection capabilities by designing and manufacturing new End-Of-Arm Tooling for cobot-mounted sensors and integrating them into the ARDS platform. Finally, and most directly, this effort updates the original ROPE software to utilize these new Rust-based libraries, extending the methodology’s application to a wider range of Air Force components.